Abstract This paper proposes an enhanced algorithm to estimate satellite DCB based on undifferenced and uncombined precise point positioning (UPPP). Our method uses UPPP and geometry-free linear combination of phase-smoothed range to extract slant ionosphere. Then we establish models to separate vertical ionospheric delay from ionospheric observations based on each single station, and assume that the sum of satellite DCBs is 0 to eliminate rank deficit. At last, DCBs and ionospheric delay are estimated simultaneously based on the weighted least squares adjustment method. However, because of the difference in the accuracy of the two types of ionospheric observations, the stochastic model suffers from the problem of weight inaccuracy. To overcome this problem, we introduce a variance component estimation method. The method iteratively adjusts the weight ratio of the two types of ionospheric observations based on the residual information, constructing a more reasonable stochastic model. The effectiveness of the algorithm is validated by observations from MGEX stations. Results show that, the satellite DCB estimation accuracy of the proposed method is 0.32 ns, which is 52.24% and 43.86% higher than that of the traditional geometry-free linear combination of phase-smoothed range method and the equal weight fusion model, respectively.
ZHANG Fan,CHAI Hongzhou,WANG Min. An Enhanced Estimation Algorithm for Satellite DCB Based on the Undifferenced and Uncombined PPP[J]. jgg, 2023, 43(8): 780-785.
ZHANG Fan,CHAI Hongzhou,WANG Min. An Enhanced Estimation Algorithm for Satellite DCB Based on the Undifferenced and Uncombined PPP[J]. jgg, 2023, 43(8): 780-785.